Founded in 2001 with the support and expertise of Switzerland's leading R&D facilities, Force Dimension has more than a decade of first-hand haptic technology expertise. Close partnerships with leaders in R&D, high-tech manufacturing and marketing enable the company to stay constantly at the cutting edge of haptic design.
Force Dimension has earned international recognition for designing and manufacturing high precision haptic interfaces operating industrial and medical robotic systems. As an example, Force Dimension provides the haptic input devices to Hansen Medical's Sensei Robotic Catheter System, a product commercialized in the USA and EU for electrophysiological beating heart procedures with force feedback. Our flagship products, the delta and omega family of haptic devices, provide best-in-class solutions that enable human operators to instinctively and safely operate critical systems.
As an engineering and service support company geared to the needs of the most demanding users, Force Dimension licenses and develops customized robotic and VR solutions for a wide range of application areas which include the medical, pharmaceutical, aerospace and entertainment industries.

role in the project: Force Dimension will work essentially for the development of the surgical interface lead by EPFL. Its contribution will be bringing its experience in medical haptics to provide support  related to the usage of the omega input device (as integrated in the DLR MIROSURG setup). More specifically, Force Dimension will develop and implement a software toolkit to drive the omega haptic device as a robotic device and to apply spatial constraints into the user's hands. Further, direct and inverse force models will be established for the electromechanical omega input device, so that external forces can be estimated through the indirect knowledge of motor torque values, even without integration of an external force sensor, thus allowing to explore architectures with increased reliability. Different model complexities will be explored, to evaluate the trade-off between computational burden (i.e. real-time compatibility) and accuracy (i.e. safety) for a given task. These models will ensure to properly identify and separate device related and human related factors.